Recent advances in Very Large Scale Integration (VLSI) circuits, microprocessors and wireless communication technologies have enabled the deployment of large scale sensor networks. In these networks, thousands of tiny sensors are distributed over a vast field to obtain fine-grained, high-precision sensing data. These sensors are typically powered by limited energy resources and communicate wirelessly.
In a typical scenario, several thousand sensors are rapidly deployed, for example, from an aircraft, in remote terrain. The sensors coordinate with each other to establish a communication network, and divide the task of mapping and monitoring the terrain amongst themselves in an energy-efficient manner. They further adapt their overall sensing to the remaining total resources, and re-organize upon sensor failure. Similarly, when additional sensors are added later, the sensors are able to reorganize themselves to take advantage of the additional sensors.
Sensors deployed to a certain region collaboratively work toward specific tasks, for example, habitat monitoring, environmental surveillance, battle field detection, and vehicle tracking. Generally, sensor network applications gather data from sources and process the gathered data. Processing is centralized or distributed. Both approaches require data dissemination. Data dissemination occurs between sources and sinks. Sources detect certain events or collect certain data. Sinks are interested in the detected events or collected data.
Frequently, sensor nodes perform local data processing such as counting, filtering, and aggregation. These operations simplify the data processing at the central data-collection point. It is radically different from conventional data networks, in which the networking layer does not understand (or care) the data content, in wireless sensor networks, the node needs to understand the data content (e.g. by communications between networking layer and application layer), so as to offload the central data processing point and optimize the use of limited resource such as battery life.
Main stream ad hoc routing protocols and Internet-based protocols are not feasible for a sensor network. First of all, they are address based. Address based routing emphasize source and destination, which is often end-to-end based. However, in sensor networks, data sinks care about data more than the destination address. In most cases, sinks do not know the destination address of a source, because any source in the target region may report an event detection. Secondly, address based routing requires a global unique address in the sensor field. Thirdly, a high density of sensors implies lengthy bits for an address field incurring a high communication overhead. Communication and energy cost is a dominant factor in sensor networks. Long address bits are inefficient for data transmission. In a typical sensor network, most sensors are expected to sleep or be inactive until they detect a certain event or receive a command to wake up. They do not require lengthy addressing bits as long as the nodes in the communication path can differentiate each other apart.
Schemes targeting data oriented network are typically termed as data dissemination. Data dissemination is required due to the resource challenges introduced by sensor networks. A few data dissemination schemes have been proposed such as SPIN, LEACH and Directed Diffusion.
Without any priori knowledge on the deployment of the sensor nodes, one assumes a flat structure of the sensor field, such as directed diffusion and SPIN. However, this may lead to inefficient use of resources, since every command must involve a full scale flooding in the sensor field. Without a structure, there is no way to define ‘regions’ or ‘interested areas’ for resource optimization purposes.
Sensor node level information including information relating to physical positioning and geographical coordinates, is often assumed by many proposed solutions of data routing and data processing in wireless sensor networks. The assumption is flawed when considering ad-hoc deployments of a large number of tiny sensors. GPS only provides coordinates to sensor nodes in a horizontal plane. For a vertical plane, such as building health monitoring, GPS coordinates do not help because some nodes have identical GPS coordinates. Also, GPS receivers are relatively expensive and are not feasible for tiny sensor nodes.
There is a desire to provide a holistic approach to route data within a sensor network using a structure which is able to optimize energy consumption. It is even more desirable that the structure assumes no geographical location information or any application specific information.